Simultaneously Sparse Solutions to Linear Inverse Problems with Multiple System Matrices and a Single Observation Vector

A problem that arises in slice-selective magnetic resonance imaging (MRI) radio-frequency (RF) excitation pulse design is abstracted as a novel linear inverse problem with a simultaneous sparsity constraint. Multiple unknown signal vectors are to be determined, where each passes through a different...

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Vydáno v:	SIAM journal on scientific computing Ročník 31; číslo 6; s. 4533 - 4579
Hlavní autoři:	Zelinski, Adam C., Goyal, Vivek K., Adalsteinsson, Elfar
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia, PA Society for Industrial and Applied Mathematics 20.01.2010
Témata:	Algebra Algebraic geometry Algorithms Approximation Exact sciences and technology Experiments Inverse problems Magnetic resonance imaging Mathematics Methods of scientific computing (including symbolic computation, algebraic computation) Numerical analysis Numerical analysis in abstract spaces Numerical analysis. Scientific computation Numerical linear algebra Performance evaluation Sciences and techniques of general use Sparsity iteratively reweighted least squares 34A55 Programming Iterative method matching pursuit Direct method Least squares method simultaneous sparse approximation 94A12 46N10 second-order cone programming Approximation Numerical linear algebra magnetic resonance imaging excitation pulse design Inverse problem 15A29 iterative shrinkage Numerical analysis Linear system Scientific computation Matrix inversion Sparse set Greedy algorithm sparse approximation multiple measurement vectors Resonance
ISSN:	1064-8275, 1095-7197
On-line přístup:	Získat plný text
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